Data Issues for Latin America Dr. Hugo G. Hidalgo School of Physics University of Costa Rica GEOSS Support for the IPCC Assessments February 2011

Hugo G. HidalgoUniversidad de Costa Rica2 Acknowledgements Thank you to GEOSS for financial support for this visit. The author is partially supported by projects VI-805-A9-22, VI-805-A9-532 and VI-808-A9-180 of the University of Costa Rica. Thank you to the School of Physics for the support to this visit. Thank you to FUNDEVI/UCR for partial additional support

Hugo G. HidalgoUniversidad de Costa Rica3 Data issues for Latin America Sources (surface observations, upper air, remote sensing) Temporal and spatial coverage (missing data) Quality control (outliers, temporal and spatial inconsistencies) Costs of data (data are in many cases not free) Availability (restricted use, release agreements) Format (including digitalization and file format, temporal and spatial resolution) Reliability (changes in station location or conditions, changes in equipment or observer, history of calibration and maintenance of instruments) Adequacy for specific uses (related to all of the above)

Hugo G. HidalgoUniversidad de Costa Rica4 Other issues for Latin America Complex topography Large variety of climates and microclimates Rich biodiversity Developing economies Vulnerable societies

Hugo G. HidalgoUniversidad de Costa Rica5 Specific uses Restrospective (hydro) climatic variability analysis Extreme events analysis (considering different time scales of floods and droughts) Detection and Attribution of climate change Climate change impacts assessments on human and environmental systems (agriculture, hydropower generation, ecology, social-economic, wildfire potential, public health, water quality and others)

Hugo G. HidalgoUniversidad de Costa Rica6 Hydrologic simulations are needed

Hugo G. HidalgoUniversidad de Costa Rica7 Streamflow data for calibration 1969 to 1979 (GRDC) Monthly streamflow gages

Hugo G. HidalgoUniversidad de Costa Rica8 LA impacts AR4 Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds. Cambridge University Press, Cambridge, UK, 976 pp

Hugo G. HidalgoUniversidad de Costa Rica9 Historical trends in rainfall Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds. Cambridge University Press, Cambridge, UK, 976 pp

Hugo G. HidalgoUniversidad de Costa Rica10 Spatial and temporal coverage CIGEFI's Network of daily precipitation stations

Hugo G. HidalgoUniversidad de Costa Rica11 Spatial and temporal coverage

Hugo G. HidalgoUniversidad de Costa Rica12 Precip significant correlation distance (degrees)

Hugo G. HidalgoUniversidad de Costa Rica13 The problem of missing necessary data Following the International Hydrological Decade (IHD, ) the number of stations in the region increased dramatically. Since the 1990s many monitoring programs have been dismantled. Satellite data cannot replace surface observations (maybe in the future) The current network does not cover large parts of the region (which have large spatial variations due to the richness of microclimates) It has not been proven that the 140 stations available in Central America during the 1980s are enough to represent climate variability adequately. Saving money by closing stations is foolish, the costs will be reflected in other items such as over-dimensioned dams and bridges or the collapse of dams and bridges.

Hugo G. HidalgoUniversidad de Costa Rica14 AVAILABILITY OF SURFACE OBSERVATIONS

Hugo G. HidalgoUniversidad de Costa Rica15 National Climatic Data Center: Global Historical Climatology Network (GHCN) Core elements: Daily precipitation, snowfall, snowdepth, tmax and tmin data. Quality controlled. Temp Precip

Hugo G. HidalgoUniversidad de Costa Rica16 Integrated Surface Database: Summary of the Day Many parameters: including daily precipitation,tmax and tmin data. Quality controlled.

Hugo G. HidalgoUniversidad de Costa Rica17 Examples of Ground-based Gridded Datasets Global Meteorological Forcing Dataset: The base meteorological data consist of daily time-series for the period of 1950 through 1999 of precipitation, maximum temperature, minimum temperature, and wind speed. Data from a variety of sources were compiled and gridded to a resolution of 1/2-degree over all global land areas. Maurer, E.P., J.C. Adam, and A.W. Wood, 2009, Climate model based consensus on the hydrologic impacts of climate change to the Rio Lempa basin of Central America, Hydrology and Earth System Sciences 13, Global Meteorological Forcing Dataset for land surface modeling: A global 50-yr ( ) dataset of meteorological forcings derived by combining reanalysis with observations. Available at 1.0-degree spatial resolution and 3-hourly, daily and monthly temporal resolution. Sheffield, J., G. Goteti, and E. F. Wood, 2006: Development of a 50-yr high-resolution global dataset of meteorological forcings for land surface modeling, J. Climate, 19 (13),

Hugo G. HidalgoUniversidad de Costa Rica18 Examples of Satellite + Ground- based Gridded Datasets CRN073: Daily and monthly precip dataset covering mesoamerica, 0.5 x 0.5 degrees, Magana et al CMAP: Global precip, Monthly 2.5 x 2.5 degrees, Xie, P. and P. A. Arkin, 1996: Analyses of Global Monthly Precipitation Using Gauge Observations, Satellite Estimates, and Numerical Model Predictions. J. Climate, 9, Xie, P. and P. A. Arkin, 1997: Global Precipitation: A 17-Year Monthly Analysis Based on Gauge Observations, Satellite Estimates and Numerical Model Outputs. BAMS, 78,

Hugo G. HidalgoUniversidad de Costa Rica19 Webber and Willmott: precip and temp From GHCN Gridded 0.5 x 0.5 degrees Monthly No tmax, tmin Extremes: Drought extremes: ok, short term events like floods: not ok

Hugo G. HidalgoUniversidad de Costa Rica20 Latin America data needs We need to estimate climate variability and work on covering all the subregions using monitoring stations. We need to develop more the use of satellite data to become less dependent of the surface data, especially in hard to reach areas. Politicians and decision-makers must provide funding to improve monitoring networks.

Hugo G. HidalgoUniversidad de Costa Rica21 Improving data issues Create regional databases from global data with homogeneous quality control Reformat data and create archives in standard format for the region Need to make inventories of data that are not free or not available in the internet Need to establish collaborations with researchers from several countries to use restricted data in regional studies More validation of satellite data is needed More integrated regional analysis of the impacts of climate change are needed Make available free data products (e.g. regional interpolated datasets) Improving modeling and monitoring networks is key More land surface and hydrologic data are needed

Hugo G. HidalgoUniversidad de Costa Rica22 Thank you!

Hugo G. HidalgoUniversidad de Costa Rica23 Need for reducing uncertainties “By the 2020s, the net increase in the number of people experiencing water stress due to climate change is likely to be between 7 and 77 million (medium confidence). While, for the second half of the century, the potential water availability reduction and the increasing demand from an increasing regional population would increase these figures to between 60 and 150 million. [13.4.3]” Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds. Cambridge University Press, Cambridge, UK, 976 pp